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Research Article

Disease mortality in domesticated animals is predicted by host evolutionary relationships

Maxwell J. Farrell and T. Jonathan Davies
PNAS April 16, 2019 116 (16) 7911-7915; first published March 29, 2019; https://doi.org/10.1073/pnas.1817323116
Maxwell J. Farrell
aDepartment of Biology, McGill University, Montreal, QC, Canada H3A 1B1;
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  • For correspondence: maxwell.farrell@mail.mcgill.ca
T. Jonathan Davies
bBotany, Forest, and Conservation Sciences, University of British Columbia, Vancouver, BC, Canada V6T 1Z4;
cBiodiversity Research Centre, University of British Columbia, Vancouver, BC, Canada V6T 1Z4;
dAfrican Centre for DNA Barcoding, University of Johannesburg, Johannesburg, South Africa 2092
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  1. Edited by Douglas Futuyma, Stony Brook University, Stony Brook, NY, and approved February 28, 2019 (received for review October 8, 2018)

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Significance

Diseases that infect domestic and wild species cause severe human health burdens and exacerbate declines of endangered species. However, we currently lack theory for predicting the mortality of multihost parasites in different hosts: Some of these diseases rarely harm their hosts, while others are nearly always fatal. Using global case-fatality data for multiple diseases of domestic mammals, we show that the evolutionary relationship among infected and susceptible hosts is a strong predictor of disease-induced mortality. We find that parasites infecting domestic species that are more evolutionarily distant from their other known hosts have a higher probability of resulting in lethal infections.

Abstract

Infectious diseases of domesticated animals impact human well-being via food insecurity, loss of livelihoods, and human infections. While much research has focused on parasites that infect single host species, most parasites of domesticated mammals infect multiple species. The impact of multihost parasites varies across hosts; some rarely result in death, whereas others are nearly always fatal. Despite their high ecological and societal costs, we currently lack theory for predicting the lethality of multihost parasites. Here, using a global dataset of >4,000 case-fatality rates for 65 infectious diseases (caused by microparasites and macroparasites) and 12 domesticated host species, we show that the average evolutionary distance from an infected host to other mammal host species is a strong predictor of disease-induced mortality. We find that as parasites infect species outside of their documented phylogenetic host range, they are more likely to result in lethal infections, with the odds of death doubling for each additional 10 million years of evolutionary distance. Our results for domesticated animal diseases reveal patterns in the evolution of highly lethal parasites that are difficult to observe in the wild and further suggest that the severity of infectious diseases may be predicted from evolutionary relationships among hosts.

  • host specificity
  • domestication
  • virulence
  • phylogeny
  • infectious disease

Footnotes

  • ↵1To whom correspondence should be addressed. Email: maxwell.farrell{at}mail.mcgill.ca.
  • Author contributions: M.J.F. and T.J.D. designed research; M.J.F. performed research; M.J.F. analyzed data; M.J.F. and T.J.D. wrote the paper; and M.J.F. organized data.

  • The authors declare no conflict of interest.

  • This article is a PNAS Direct Submission.

  • Data deposition: The data and code necessary to reproduce our analyses have been deposited in Figshare (doi:10.6084/m9.figshare.7497137).

  • This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1817323116/-/DCSupplemental.

Published under the PNAS license.

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Disease mortality in domesticated animals is predicted by host evolutionary relationships
Maxwell J. Farrell, T. Jonathan Davies
Proceedings of the National Academy of Sciences Apr 2019, 116 (16) 7911-7915; DOI: 10.1073/pnas.1817323116

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Disease mortality in domesticated animals is predicted by host evolutionary relationships
Maxwell J. Farrell, T. Jonathan Davies
Proceedings of the National Academy of Sciences Apr 2019, 116 (16) 7911-7915; DOI: 10.1073/pnas.1817323116
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Proceedings of the National Academy of Sciences: 116 (16)
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